Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models
In this study, the frequency ratio and logistic regression models are applied and verified for the analysis of debris flow susceptibility in a portion of the Dry Frontal Andes and Occidental Preandes of San Juan at approximately 30°S latitude, through aninvestigation based on a Geographic Informatio...
- Autores:
-
Esper, Maria Yanina
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/72739
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/72739
http://bdigital.unal.edu.co/37214/
http://bdigital.unal.edu.co/37214/2/
- Palabra clave:
- Debris flows susceptibility
GIS
San Juan
Argentina
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
id |
UNACIONAL2_f082b8cf8d9591f4adcbe162af72df58 |
---|---|
oai_identifier_str |
oai:repositorio.unal.edu.co:unal/72739 |
network_acronym_str |
UNACIONAL2 |
network_name_str |
Universidad Nacional de Colombia |
repository_id_str |
|
dc.title.spa.fl_str_mv |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
title |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
spellingShingle |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models Debris flows susceptibility GIS San Juan Argentina |
title_short |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
title_full |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
title_fullStr |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
title_full_unstemmed |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
title_sort |
Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models |
dc.creator.fl_str_mv |
Esper, Maria Yanina |
dc.contributor.author.spa.fl_str_mv |
Esper, Maria Yanina |
dc.subject.proposal.spa.fl_str_mv |
Debris flows susceptibility GIS San Juan Argentina |
topic |
Debris flows susceptibility GIS San Juan Argentina |
description |
In this study, the frequency ratio and logistic regression models are applied and verified for the analysis of debris flow susceptibility in a portion of the Dry Frontal Andes and Occidental Preandes of San Juan at approximately 30°S latitude, through aninvestigation based on a Geographic Information System (GIS). The site under study covers an area of 2175.9 km2 with a debris flow area of 42.45 km2. For this purpose, thematic layers including debris flow inventory, lithology, elevation, slope, aspect, and solar radiation were used. The debris flow inventory map was prepared by interpreting aerial photographs and satellite images and was supported by field surveys. Lithology was extracted from an existing geological map. Slope, aspect and solar radiation were calculated from a Digital Elevation Model created from SRTM (Shuttle Radar Topographic Mission) and topographical maps. The relationship between the variables and the debris flow inventory was calculated using the frequency ratio and logistic regression models. Both models helped to produce debris flow susceptibility maps that classified susceptibility into five categories: very low, low, moderate, high and very high. Subsequently, each debris flow susceptibility map was compared with known debris flow locations and tested. The frequency ratio model (accuracy is 82.71%) was more accurate than the logistic regression model (accuracy is 75.64%) for predictons of the high and very high categories. ResumenEn este trabajo se aplican, mediante el uso de Sistemas de Información Geográfica, dos modelos estadísticos en la evaluación de la susceptibilidad del terreno a la ocurrencia de flujos de detritos, la relación de frecuencias (Fr) y la regresión logística. El área de estudio comprende un sector de Cordillera Frontal y de Precordillera Occidental a los 30°S de latitud media. Se crearon mapas de elevación, pendiente, insolación, orientaciones, estratigrafía y un inventario de flujos de detritos. Este último, a partir de la interpretación y análisis digital de fotografías aéreas e imágenes satelitales. La estratigrafía fue obtenida a partir de cartas geologicas preexistentes. Las pendientes, orientaciones e insolación fueron calculadas, a partir de un modelo digital de elevaciones. Los mapas de susceptibilidad generados han sido reclasificados en cinco categorías: muy baja, baja, moderada, alta y muy alta. Finalmente, estos mapas, fueron validados espacialmente y como resultado se observa que el modelo Fr predice mejor (82,71%) que la regresión logística (75,64%) para las clases alta y muy alta. |
publishDate |
2013 |
dc.date.issued.spa.fl_str_mv |
2013 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-03T15:30:28Z |
dc.date.available.spa.fl_str_mv |
2019-07-03T15:30:28Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/72739 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/37214/ http://bdigital.unal.edu.co/37214/2/ |
url |
https://repositorio.unal.edu.co/handle/unal/72739 http://bdigital.unal.edu.co/37214/ http://bdigital.unal.edu.co/37214/2/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.spa.fl_str_mv |
http://revistas.unal.edu.co/index.php/esrj/article/view/38925 |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Earth Sciences Research Journal Earth Sciences Research Journal |
dc.relation.ispartofseries.none.fl_str_mv |
Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) 2339-3459 1794-6190 |
dc.relation.references.spa.fl_str_mv |
Esper, Maria Yanina (2013) Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models. Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) 2339-3459 1794-6190 . |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
UNIVERSIDAD NACIONAL DE COLOMBIA |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/72739/1/38925-173503-2-SP.doc https://repositorio.unal.edu.co/bitstream/unal/72739/2/38925-173502-2-SP.doc https://repositorio.unal.edu.co/bitstream/unal/72739/3/38925-173504-1-SP.jpg https://repositorio.unal.edu.co/bitstream/unal/72739/4/38925-200339-1-PB.pdf https://repositorio.unal.edu.co/bitstream/unal/72739/5/38925-173506-2-SP.jpg https://repositorio.unal.edu.co/bitstream/unal/72739/6/38925-173507-1-SP.jpg https://repositorio.unal.edu.co/bitstream/unal/72739/7/38925-173505-1-SP.jpg https://repositorio.unal.edu.co/bitstream/unal/72739/8/38925-200339-1-PB.pdf.jpg |
bitstream.checksum.fl_str_mv |
9db4b9d7ff01e9e767e065702d90483a d30f801074b7529333808bb4d2c7d05e e86914023258a37ea9b8bc404128e9e7 ec748422b4a221d883e19eba416c97b6 d8ef460c8310a6a26dd9cd6089784f12 c90cccbee40b0ce984d3ff3df1a3d6b4 d87a69964ef3035c33491ac4dcbb1d4d da5da76a24fc658271ffb45346bec359 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
_version_ |
1814089627480358912 |
spelling |
Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Esper, Maria Yaninac4a9bc13-d730-468d-88cb-a7b24b13db2b3002019-07-03T15:30:28Z2019-07-03T15:30:28Z2013https://repositorio.unal.edu.co/handle/unal/72739http://bdigital.unal.edu.co/37214/http://bdigital.unal.edu.co/37214/2/In this study, the frequency ratio and logistic regression models are applied and verified for the analysis of debris flow susceptibility in a portion of the Dry Frontal Andes and Occidental Preandes of San Juan at approximately 30°S latitude, through aninvestigation based on a Geographic Information System (GIS). The site under study covers an area of 2175.9 km2 with a debris flow area of 42.45 km2. For this purpose, thematic layers including debris flow inventory, lithology, elevation, slope, aspect, and solar radiation were used. The debris flow inventory map was prepared by interpreting aerial photographs and satellite images and was supported by field surveys. Lithology was extracted from an existing geological map. Slope, aspect and solar radiation were calculated from a Digital Elevation Model created from SRTM (Shuttle Radar Topographic Mission) and topographical maps. The relationship between the variables and the debris flow inventory was calculated using the frequency ratio and logistic regression models. Both models helped to produce debris flow susceptibility maps that classified susceptibility into five categories: very low, low, moderate, high and very high. Subsequently, each debris flow susceptibility map was compared with known debris flow locations and tested. The frequency ratio model (accuracy is 82.71%) was more accurate than the logistic regression model (accuracy is 75.64%) for predictons of the high and very high categories. ResumenEn este trabajo se aplican, mediante el uso de Sistemas de Información Geográfica, dos modelos estadísticos en la evaluación de la susceptibilidad del terreno a la ocurrencia de flujos de detritos, la relación de frecuencias (Fr) y la regresión logística. El área de estudio comprende un sector de Cordillera Frontal y de Precordillera Occidental a los 30°S de latitud media. Se crearon mapas de elevación, pendiente, insolación, orientaciones, estratigrafía y un inventario de flujos de detritos. Este último, a partir de la interpretación y análisis digital de fotografías aéreas e imágenes satelitales. La estratigrafía fue obtenida a partir de cartas geologicas preexistentes. Las pendientes, orientaciones e insolación fueron calculadas, a partir de un modelo digital de elevaciones. Los mapas de susceptibilidad generados han sido reclasificados en cinco categorías: muy baja, baja, moderada, alta y muy alta. Finalmente, estos mapas, fueron validados espacialmente y como resultado se observa que el modelo Fr predice mejor (82,71%) que la regresión logística (75,64%) para las clases alta y muy alta.application/pdfspaUNIVERSIDAD NACIONAL DE COLOMBIAhttp://revistas.unal.edu.co/index.php/esrj/article/view/38925Universidad Nacional de Colombia Revistas electrónicas UN Earth Sciences Research JournalEarth Sciences Research JournalEarth Sciences Research Journal; Vol. 17, núm. 2 (2013) Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) 2339-3459 1794-6190Esper, Maria Yanina (2013) Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression models. Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) Earth Sciences Research Journal; Vol. 17, núm. 2 (2013) 2339-3459 1794-6190 .Debris flow susceptibility mapping in a portion of the andes and preandes of san juan, argentina using frequency ratio and logistic regression modelsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTDebris flows susceptibilityGISSan JuanArgentinaORIGINAL38925-173503-2-SP.docapplication/msword69632https://repositorio.unal.edu.co/bitstream/unal/72739/1/38925-173503-2-SP.doc9db4b9d7ff01e9e767e065702d90483aMD5138925-173502-2-SP.docapplication/msword29696https://repositorio.unal.edu.co/bitstream/unal/72739/2/38925-173502-2-SP.docd30f801074b7529333808bb4d2c7d05eMD5238925-173504-1-SP.jpgimage/jpeg1021634https://repositorio.unal.edu.co/bitstream/unal/72739/3/38925-173504-1-SP.jpge86914023258a37ea9b8bc404128e9e7MD5338925-200339-1-PB.pdfapplication/pdf9296985https://repositorio.unal.edu.co/bitstream/unal/72739/4/38925-200339-1-PB.pdfec748422b4a221d883e19eba416c97b6MD5438925-173506-2-SP.jpgimage/jpeg956937https://repositorio.unal.edu.co/bitstream/unal/72739/5/38925-173506-2-SP.jpgd8ef460c8310a6a26dd9cd6089784f12MD5538925-173507-1-SP.jpgimage/jpeg1013672https://repositorio.unal.edu.co/bitstream/unal/72739/6/38925-173507-1-SP.jpgc90cccbee40b0ce984d3ff3df1a3d6b4MD5638925-173505-1-SP.jpgimage/jpeg1477868https://repositorio.unal.edu.co/bitstream/unal/72739/7/38925-173505-1-SP.jpgd87a69964ef3035c33491ac4dcbb1d4dMD57THUMBNAIL38925-200339-1-PB.pdf.jpg38925-200339-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg7748https://repositorio.unal.edu.co/bitstream/unal/72739/8/38925-200339-1-PB.pdf.jpgda5da76a24fc658271ffb45346bec359MD58unal/72739oai:repositorio.unal.edu.co:unal/727392023-06-25 23:04:22.373Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |